CN105374231A - Early warning method, device and system - Google Patents

Abstract

The embodiment of the present invention discloses an early warning method, a device and a system. The method comprises a step of predicting the movement trajectories of a first object and a second object respectively, a step of determining the existence of a first time length according to the trajectories of the first object and the second object such that the early warning of the first object and/or the second object is carried out when the distance between the first object and the second object is not larger than a first preset value after the first time length. According to the technical scheme of the embodiment of the present invention, the automatic early warning of vehicles or pedestrians can be realized, and thus the probability of traffic accidents can be effectively reduced.

Description

A kind of early warning method, device and system

technical field

The present invention relates to the field of Internet of Vehicles, in particular to an early warning method, device and system.

Background technique

In recent years, with the widening of the road surface, the increase of the number of lanes, the sharp increase of the traffic flow, coupled with various complex conditions on the road surface, it has brought certain difficulties for cars to pass through the intersection. Correspondingly, how to solve the safety problem of pedestrians around the driving vehicle is becoming more and more important.

In this regard, the current safety warning scheme is usually to detect whether there are pedestrians within a certain range around the vehicle in real time by setting up an induction detection device, and if there are pedestrians around the vehicle detected, a warning message will be sent to the driver.

The above-mentioned technical scheme of setting up an inductive detection device to detect in real time whether there are pedestrians within a certain range around the vehicle, and if a pedestrian is detected around the vehicle, then send a warning message to the driver, although the warning function can be realized to a certain extent, but usually The working distance and range of the induction detection device are limited. Therefore, even if the presence of pedestrians is detected, there may not be sufficient reaction time and operation time for the driver at this time, which leads to the inability to truly play the actual role of safety warning and cannot be effective. Avoid traffic accidents.

Contents of the invention

In view of this, in order to solve the existing technical problems, the embodiments of the present invention provide:

A method of early warning, including:

respectively predicting the movement trajectories of the first object and the second object;

According to the movement trajectories of the first object and the second object, it is determined that there is a first duration, so that after the first duration, when the distance between the first object and the second object is not greater than a first preset value, An early warning is issued to the first object and/or the second object.

Preferably, the trajectory of the predicted object includes:

Obtaining object information collected by multiple collection devices and location information of the collection devices;

Estimate the moving speed and direction of the object according to the obtained object information and the location information of the collection device;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Preferably, the trajectory of the predicted object includes:

According to the GPS installed or carried by the object, the object is positioned multiple times, and the location information and time information of the object are obtained respectively;

Estimate the moving speed and direction of the object according to the acquired object position information and time information;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Preferably, the trajectory of the predicted object includes:

When it is determined that the object is currently using the navigation function, the moving track of the object is predicted according to the navigation route.

Preferably, the trajectory of the predicted object includes:

According to the current moment and the position information of the object, as well as the historical experience information, the moving trajectory of the object is predicted, wherein the historical experience information involves the corresponding relationship between the time period information and the moving trajectory of the object.

Preferably, after predicting the moving trajectories of the first object and the second object, the method further includes: processing the moving trajectories of the first object and/or the second object based on extended Kalman filter, and the processed first object The trajectory of movement of an object and/or a second object is used to determine whether the first duration exists.

Preferably, the giving an early warning to the first object and/or the second object includes:

The first object and/or the second object are given an early warning according to the first duration and a preset early warning strategy, wherein the early warning strategy distinguishes warning levels, and the shorter the first time period, the higher the corresponding early warning level.

Preferably, the early warning includes one or more of the following:

Send warning information to terminal equipment;

Display a warning message;

Play warning sound;

Activate the brakes.

Preferably, the first object is a vehicle or a pedestrian, and the second object is a vehicle or a pedestrian.

An early warning device, comprising: a first prediction module, a second prediction module, a judgment module and an early warning module; wherein,

The first prediction module is used to predict the movement trajectory of the first object;

The second prediction module is used to predict the movement trajectory of the second object;

The judging module is configured to judge whether there is a first duration according to the prediction results of the first prediction module and the second prediction module, so that after the first duration, the distance between the first object and the second object does not greater than the first preset value;

The early warning module is configured to, when the judging module determines that there is a first duration, so that after the first duration, the distance between the first object and the second object is not greater than a first preset value, A subject and/or a second subject is alerted.

Preferably, the first prediction module and/or the second prediction module are specifically used for:

Obtaining object information collected by multiple collection devices and location information of the collection devices;

Estimate the moving speed and direction of the object according to the obtained object information and the location information of the acquisition device;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Preferably, the first prediction module and/or the second prediction module are specifically used for:

According to the GPS installed or carried by the object, the object is positioned multiple times, and the location information and time information of the object are obtained respectively;

Estimate the moving speed and direction of the object according to the acquired object position information and time information;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Preferably, the first prediction module and/or the second prediction module are specifically used for:

When it is determined that the object is currently using the navigation function, the moving track of the object is predicted according to the navigation route.

Preferably, the first prediction module and/or the second prediction module are specifically used for:

According to the current moment and the position information of the object, as well as the historical experience information, the moving trajectory of the object is predicted, wherein the historical experience information involves the corresponding relationship between the time period information and the moving trajectory of the object.

Preferably, the device also includes an optimization processing module,

The optimization processing module is used to process the movement trajectory of the first object and/or the second object predicted by the first prediction module and/or the second prediction module based on the extended Kalman filter, and the processed first object And/or the moving trajectory of the second object is used to determine whether the first duration exists.

Preferably, the early warning module is specifically configured to give early warning to the first object and/or the second object according to a first duration and a preset early warning strategy, wherein the early warning strategy distinguishes between warning levels, and the first duration The smaller the value, the higher the corresponding warning level.

Preferably, the early warning module is specifically used for early warning in one or more of the following ways:

Send warning information to terminal equipment;

Display a warning message;

Play warning sound;

Activate the brakes.

An early warning system, comprising: an early warning device, a first object and a second object; wherein,

The early warning device is the early warning device described in any one of claims 10-17.

Preferably, the first object is a vehicle or a pedestrian, and the second object is a vehicle or a pedestrian.

In the early warning method, device and system described in the embodiments of the present invention, according to the movement trajectories of the first object and the second object, it is determined that there is a first duration, so that after the first duration, the distance between the first object and the second object When the distance between them is not greater than the first preset value, an early warning is given to the first object and/or the second object. The technical solutions described in the embodiments of the present invention can realize automatic early warning for vehicles or pedestrians, thereby effectively reducing the probability of traffic accidents.

Description of drawings

Fig. 1 is a schematic flow chart of an early warning method according to an embodiment of the present invention;

Fig. 2 is a schematic structural diagram of an early warning device according to an embodiment of the present invention;

Fig. 3 is a schematic structural diagram of another early warning device according to the embodiment of the present invention;

4 is a schematic flow chart of the early warning method described in Embodiment 1 of the present invention;

Fig. 5 is a schematic structural diagram of an early warning device corresponding to Embodiment 1 of the present invention;

FIG. 6 is a schematic diagram of processing based on extended Kalman filter vehicle trajectories according to Embodiment 1 of the present invention.

detailed description

Fig. 1 is a kind of early warning method of the embodiment of the present invention, it is characterized in that, this method comprises:

Step 11: Predict the moving trajectories of the first object and the second object respectively;

Step 12: According to the moving trajectories of the first object and the second object, determine that there is a first duration, so that after the first duration, the distance between the first object and the second object is not greater than a first preset value, an early warning is given to the first object and/or the second object.

It should be noted that, according to the moving trajectories of the first object and the second object, if it is determined that the first duration does not exist, no warning is required.

Optionally, in an embodiment of the present invention, the predicted movement trajectory of the object includes:

Obtaining object information collected by multiple collection devices and location information of the collection devices;

Estimate the moving speed and direction of the object according to the obtained object information and the location information of the acquisition device;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Optionally, in an embodiment of the present invention, the predicted movement trajectory of the object includes:

According to the GPS installed or carried by the object, the object is positioned multiple times, and the location information and time information of the object are obtained respectively;

Estimate the moving speed and direction of the object according to the acquired object position information and time information;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Optionally, in an embodiment of the present invention, the predicted movement trajectory of the object includes:

When it is determined that the object is currently using the navigation function, the moving track of the object is predicted according to the navigation route.

Optionally, in an embodiment of the present invention, the predicted movement trajectory of the object includes:

According to the current moment and the position information of the object, as well as the historical experience information, the moving trajectory of the object is predicted, wherein the historical experience information involves the corresponding relationship between the time period information and the moving trajectory of the object.

It should be noted that the current information described in the embodiments of the present invention does not specifically refer to the information at the current time, but the information at the current time and a period of time before that, while the historical information refers to the information at a considerable period of time before the current time .

In addition, the above-mentioned "object" includes the first object and/or the second object.

Optionally, in an embodiment of the present invention, after the prediction of the movement trajectories of the first object and the second object, the method further includes: based on the extended Kalman filter, the movement trajectories of the first object and/or the second object Processing is performed, and the processed movement tracks of the first object and/or the second object are used to determine whether there is a first duration.

Optionally, in an embodiment of the present invention, the giving an early warning to the first object and/or the second object includes:

The first object and/or the second object are given an early warning according to the first duration and a preset early warning strategy, wherein the early warning strategy distinguishes warning levels, and the shorter the first time period, the higher the corresponding early warning level.

Optionally, in an embodiment of the present invention, the early warning includes one or more of the following:

Send warning information to terminal equipment;

Display a warning message;

Play warning sound;

Activate the brakes.

Optionally, in an embodiment of the present invention, the first object is a vehicle or a pedestrian, and the second object is a vehicle or a pedestrian.

The embodiment of the present invention also correspondingly proposes an early warning device, as shown in Figure 2, the early warning device includes: a first prediction module 21, a second prediction module 22, a judgment module 23 and an early warning module 24; wherein,

The first prediction module 21 is configured to predict the movement trajectory of the first object;

The second prediction module 22 is configured to predict the movement trajectory of the second object;

The judging module 23 is configured to judge whether there is a first duration according to the prediction results of the first prediction module 21 and the second prediction module 22, so that after the first duration, the distance between the first object and the second object The distance is not greater than the first preset value;

The early warning module 24 is configured to, when the judging module 23 determines that there is a first duration, so that after the first duration, the distance between the first object and the second object is not greater than a first preset value, The first object and/or the second object are given an early warning.

Optionally, in an embodiment of the present invention, the first prediction module 21 and/or the second prediction module 22 are specifically used for:

Obtaining object information collected by multiple collection devices and location information of the collection devices;

Estimate the moving speed and direction of the object according to the obtained object information and the location information of the collection device;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Optionally, in an embodiment of the present invention, the first prediction module 21 and/or the second prediction module 22 are specifically used for:

According to the GPS installed or carried by the object, the object is positioned multiple times, and the location information and time information of the object are obtained respectively;

Estimate the moving speed and direction of the object according to the acquired object position information and time information;

Based on the estimated moving speed and direction, predict the moving trajectory of the object.

Optionally, in an embodiment of the present invention, the first prediction module 21 and/or the second prediction module 22 are specifically used for:

When it is determined that the object is currently using the navigation function, the moving track of the object is predicted according to the navigation route.

Optionally, in an embodiment of the present invention, the first prediction module 21 and/or the second prediction module 22 are specifically used for:

According to the current moment and the position information of the object, as well as the historical experience information, the moving trajectory of the object is predicted, wherein the historical experience information involves the corresponding relationship between the time period information and the moving trajectory of the object.

Optionally, as shown in FIG. 3, in an embodiment of the present invention, the device further includes an optimization processing module 25,

The optimization processing module 25 is configured to process the movement trajectory of the first object and/or the second object predicted by the first prediction module 21 and/or the second prediction module 22 based on the extended Kalman filter, and the processed The movement trajectory of the first object and/or the second object is used to determine whether the first duration exists.

Optionally, in an embodiment of the present invention, the early warning module 24 is specifically configured to give an early warning to the first object and/or the second object according to the first duration and a preset early warning strategy, wherein the The above early warning strategy distinguishes the early warning levels. The shorter the first time period, the higher the corresponding early warning level.

Optionally, in an embodiment of the present invention, the early warning module 24 is specifically configured to use one or more of the following methods for early warning:

Send warning information to terminal equipment;

Display a warning message;

Play warning sound;

Activate the brakes.

The embodiment of the present invention also correspondingly proposes an early warning system, which includes: an early warning device, a first object, and a second object; wherein, the early warning device is the above-mentioned early warning device (corresponding to FIG. 2 and FIG. 3 ).

Optionally, in an embodiment of the present invention, the first object is a vehicle or a pedestrian, and the second object is a vehicle or a pedestrian.

The technical solution of the present invention will be further described in detail through specific examples below.

Example 1

In this embodiment, the first object is a pedestrian, and the second object is a vehicle. The first prediction module 21 corresponds to the pedestrian collection module, the second prediction module 22 corresponds to the vehicle collection module, and the judgment module 23 corresponds to the safety prediction module.

Figure 4 is a schematic flowchart of the early warning method described in Embodiment 1 of the present invention, and Figure 5 is a schematic structural diagram of the early warning device corresponding to Embodiment 1 of the present invention, referring to Figures 4 and 5, the process includes:

Step 41: The pedestrian collection module predicts the movement trajectory of the pedestrian according to the current information of the pedestrian collected at the current intersection.

In practical application scenarios, multiple camera devices can be installed equidistantly within a certain range around the intersection, so as to estimate the moving speed and direction of pedestrians based on the pedestrian information collected by each camera device and the location information of each camera device. Or, in practical applications, since people usually carry terminal equipment, the terminal carried by the user can be positioned by GPS, and then the current position of the pedestrian at each time can be obtained, and then according to the change of the user's position within a certain time interval, Predict the movement trajectory of pedestrians.

Step 42: The vehicle collection module collects the current information of the vehicles driving near the intersection in real time, and predicts the movement trajectory of the vehicles according to the current information.

First, the simplest and most direct method is to detect whether the vehicle is currently using the navigation function, and if so, the next trajectory of the vehicle can be determined according to its current navigation route. However, if the vehicle does not currently have a navigation service enabled, other solutions need to be used to predict the trajectory of the vehicle. For the above problems, there are the following solutions as follows:

Now, most vehicles will be equipped with GPS, and the location of the vehicle at the current moment can be obtained in real time through GPS. Then, through a large number of collections of the location of the vehicle at each historical moment, and then according to the collected information, through the wavelet neural network algorithm or specific The data processing method, etc., can learn to obtain the route that the vehicle frequently travels in a specific period of time every day. Taking people's daily life habits as an example, the user drives a vehicle from home to the work route from 7:00 to 8:00 every morning from Monday to Friday, that is to say, the user's vehicle The driving track from 7:00 am to 8:00 am is repeated, that is, the user's route to work. In this solution, by summarizing the repeated driving route of the vehicle in a specific period of time every day, the driving trajectory of the vehicle can be predicted according to the current moment and the location of the vehicle. Based on the above example, assuming that the current driving time of the vehicle is 7:30 am on Tuesday, and the current location of the vehicle is on the route to work, it can be determined that the next driving track of the user will be the route to work that has not been traveled. Therefore, the trajectory of the vehicle can be predicted.

Further, for the above solution, further precise processing of the vehicle track can also be performed based on an Extended Kalman Filter (Extended Kalman Filter, EKF).

Referring to Figure 6 for the basic block diagram of processing, it can be seen that the current information of the vehicle can be obtained by the positioning system, gyroscope, steering angle sensor, speed sensor, and acceleration sensor. Specifically, the state equation of the vehicle needs to be established first, assuming that the vehicle state vector is X, and the measurement vector is Z, and each includes six vehicle state information, for example, the abscissa y of the vehicle center of mass, the ordinate x of the center of mass, and the longitudinal vehicle speed v, Heading (the angle between the speed and the x-axis, clockwise), the longitudinal acceleration of the vehicle α, the yaw rate of the vehicle Therefore, the measurement equation is obtained by Z(k)=C〞(X(k),k)+ν(k)=X(k)+ν(k), and the vehicle state vector at time t0 is: And according to the above equation, the vehicle state prediction formula is obtained.

After the system state equation and measurement equation are established, the initial state vector, covariance and error covariance matrix of the vehicle need to be initialized. Specifically, the vehicle initialization state vector can be preliminarily estimated based on the actual vehicle state, and each parameter in the covariance can be adjusted and analyzed by using Matlab software based on multiple tests or simulation results, and then determined after optimization.

The aforementioned extended Kalman filter method is further used to filter the collected vehicle positioning and running state data, which can continuously correct the vehicle motion state and improve the positioning accuracy, thereby further improving the accuracy of vehicle trajectory prediction.

Step 43: The safety prediction module detects whether there is a first time period according to the movement trajectories of the pedestrian and the vehicle, so that after the first time period, the vehicle and the pedestrian are in the same position, or there is a distance between the two The distance is within the preset first distance.

Specifically, according to the motion trajectories of the pedestrian and the vehicle relative to the time parameter, it is possible to estimate whether there is an intersection point between the two motion trajectories, or whether the distance between the closest points between the two functions is less than or equal to the first distance. If there is an intersection, or the distance is less than or equal to the first distance, that is to say, there is a possibility of a traffic accident between the vehicle and the pedestrian. Among them, the setting of the first distance is to better protect the safety of vehicles and pedestrians, because in a certain situation, if the distance between the vehicle and pedestrians is too close, it is easy to cause traffic accidents.

It should be noted that the intersection between the vehicle and the pedestrian is equivalent to the first distance being 0.

Step 44: If it exists, the security early warning module takes corresponding early warning processing measures according to the time length of the first time period.

Specifically, multiple warning levels may be set according to preset time thresholds. And it is assumed that the more urgent the early warning measures need to be taken, the higher the early warning level, and correspondingly, the shorter the time threshold. For example, the warning level is divided into three levels, the first time threshold corresponding to the first level is 3 minutes, the second time threshold corresponding to the second level is 20s, and the third time threshold corresponding to the third level is 3s.

When the first duration is not less than the preset first time threshold, an avoidance warning message is sent to the pedestrian. For example, a warning message is sent to the pedestrian's terminal, or a warning message is displayed to the pedestrian through its own display device.

When the first time length is less than the first time threshold and not less than the preset second time threshold, a warning message is sent to the vehicle, and the whistle equipment of the vehicle is activated to warn the vehicle located in the Pedestrians near the vehicle.

When the first time length is less than the second time threshold, a warning message is sent to the vehicle, and a brake device of the vehicle is activated.

The early warning method and device described in the embodiments of the present invention obtain the moving states of vehicles and pedestrians in real time, predict the trajectory and safety level of vehicles and pedestrians, and adopt corresponding technical solutions for early warning processing according to different safety levels to realize Automatic early warning of vehicles or pedestrians can effectively reduce the probability of traffic accidents.

Each module described in the present invention can be implemented by a central processing unit (Central Processing Unit, CPU), a digital signal processor (Digital Signal Processor, DSP) or a programmable logic array (Field-Programmable Gate Array, FPGA) in the electronic device.

Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, systems, or computer program products. Accordingly, the present invention can take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the protection scope of the present invention.

Claims (19)

1. A method for early warning, characterized in that the method comprises: respectively predicting the movement trajectories of the first object and the second object; According to the movement trajectories of the first object and the second object, it is determined that there is a first duration, so that after the first duration, when the distance between the first object and the second object is not greater than a first preset value, An early warning is issued to the first object and/or the second object. 2. The method according to claim 1, wherein the trajectory of the predicted object comprises: Obtaining object information collected by multiple collection devices and location information of the collection devices; Estimate the moving speed and direction of the object according to the obtained object information and the location information of the acquisition device; Based on the estimated moving speed and direction, predict the moving trajectory of the object. 3. The method according to claim 1, wherein the moving track of the predicted object comprises: According to the GPS installed or carried by the object, the object is positioned multiple times, and the location information and time information of the object are obtained respectively; Estimate the moving speed and direction of the object according to the acquired object position information and time information; Based on the estimated moving speed and direction, predict the moving trajectory of the object. 4. The method according to claim 1, wherein the trajectory of the predicted object comprises: When it is determined that the object is currently using the navigation function, the moving track of the object is predicted according to the navigation route. 5. The method according to claim 1, wherein the moving track of the predicted object comprises: According to the current moment and the position information of the object, as well as the historical experience information, the moving trajectory of the object is predicted, wherein the historical experience information involves the corresponding relationship between the time period information and the moving trajectory of the object. 6. The method according to any one of claims 1 to 5, characterized in that, after the prediction of the moving trajectories of the first object and the second object, the method further comprises: based on Extended Kalman Filtering, the first object and the second object and/or the movement trajectory of the second object is processed, and the processed movement trajectory of the first object and/or the second object is used to determine whether there is a first duration. 7. The method according to any one of claims 1 to 5, wherein the giving an early warning to the first object and/or the second object comprises: The first object and/or the second object are given an early warning according to the first duration and a preset early warning strategy, wherein the early warning strategy distinguishes warning levels, and the shorter the first time period, the higher the corresponding early warning level. 8. The method according to any one of claims 1 to 5, wherein the early warning includes one or more of the following: Send warning information to terminal equipment; Display a warning message; Play warning sound; Activate the brakes. 9. The method according to any one of claims 1 to 5, characterized in that, The first object is a vehicle or a pedestrian, and the second object is a vehicle or a pedestrian. 10. An early warning device, characterized in that the early warning device comprises: a first prediction module, a second prediction module, a judgment module and an early warning module; wherein, The first prediction module is used to predict the movement trajectory of the first object; The second prediction module is used to predict the movement trajectory of the second object; The judging module is configured to judge whether there is a first duration according to the prediction results of the first prediction module and the second prediction module, so that after the first duration, the distance between the first object and the second object does not greater than the first preset value; The early warning module is configured to, when the judging module determines that there is a first duration, so that after the first duration, the distance between the first object and the second object is not greater than a first preset value, A subject and/or a second subject is alerted. 11. The device according to claim 10, wherein the first prediction module and/or the second prediction module are specifically used for: Obtaining object information collected by multiple collection devices and location information of the collection devices; Estimate the moving speed and direction of the object according to the obtained object information and the location information of the acquisition device; Based on the estimated moving speed and direction, predict the moving trajectory of the object. 12. The device according to claim 10, wherein the first prediction module and/or the second prediction module are specifically used for: According to the GPS installed or carried by the object, the object is positioned multiple times, and the location information and time information of the object are obtained respectively; Estimate the moving speed and direction of the object according to the acquired object position information and time information; Based on the estimated moving speed and direction, predict the moving trajectory of the object. 13. The device according to claim 10, wherein the first prediction module and/or the second prediction module are specifically used for: When it is determined that the object is currently using the navigation function, the moving track of the object is predicted according to the navigation route. 14. The device according to claim 10, wherein the first prediction module and/or the second prediction module are specifically used for: According to the current moment and the position information of the object, as well as the historical experience information, the moving trajectory of the object is predicted, wherein the historical experience information involves the corresponding relationship between the time period information and the moving trajectory of the object. 15. The device according to any one of claims 10 to 14, characterized in that the device further comprises an optimization processing module, The optimization processing module is used to process the movement trajectory of the first object and/or the second object predicted by the first prediction module and/or the second prediction module based on the extended Kalman filter, and the processed first object And/or the moving trajectory of the second object is used to determine whether the first duration exists. 16. Apparatus according to any one of claims 10 to 14, wherein The early warning module is specifically configured to give early warning to the first object and/or the second object according to the first duration and a preset early warning strategy, wherein the early warning strategy distinguishes between early warning levels, the shorter the first duration, the The corresponding warning level is higher. 17. The device according to any one of claims 10 to 14, characterized in that, the early warning module is specifically used for early warning in one or more of the following ways: Send warning information to terminal equipment; Display a warning message; Play warning sound; Activate the brakes. 18. An early warning system, characterized in that the early warning system comprises: an early warning device, a first object and a second object; wherein, The early warning device is the early warning device described in any one of claims 10-17. 19. The system of claim 18, wherein: The first object is a vehicle or a pedestrian, and the second object is a vehicle or a pedestrian.